Grewal, Harpreet

Background Artificial intelligence (AI) and large language models (LLMs), are potential tools for enhancing healthcare delivery and clinical research. Presently, there is a scarcity of research regarding the viewpoints of medical students toward LLMs. This study aims to explore the perceptions of LLMs and their applications among this demographic. Methods A cross-sectional study was done using an online survey. It was designed using Google Forms and circulated from July 2023 to August 2023. The target population included medical students from Ecuador, Ethiopia, India, Mauritius, Pakistan, United Arab Emirates (UAE), and the United States (USA). Results A total of 1180 responses were collected from 10 medical colleges across 7 countries. The UAE had the largest number of responses (31.7%), followed by Ecuador (17.6%), and Mauritius (13.7%). And 77.4% respondents were already aware about LLMs before attempting the survey, most popularly, ChatGPT. Participants were most familiar with the specific use of LLMs in research (46%), and the lowest familiarity was seen in the use of LLMs in healthcare (37%). More than half of the participants (52%) support the use of LLMs healthcare, yet a significant number of them remained neutral (37%) or disagreed (31%) on LLMs being safe in this context. Conclusion While most of the medical students are aware of LLMs and their applications, the multinational survey demonstrated hesitancy among medical students in fully adopting LLMs into healthcare practice and clinical research. This study prompts further exploration of medical students’ attitudes and acceptance concerning the integration of LLMs for research methodologies, ethical considerations, and healthcare practice.

The AI-MIRACLE Study investigates the efficacy of using ChatGPT 4.0, a large language model (LLM), for translating and simplifying radiology reports into multiple languages, aimed at enhancing patient comprehension. The study assesses the model’s performance across the most spoken languages in the U.S., emphasizing the accuracy and clarity of translated and simplified radiology reports for non-medical readers. This study employed ChatGPT 4.0 to translate and simplify selected radiology reports into Vietnamese, Tagalog, Spanish, Mandarin, and Arabic. Hindi was used as a preliminary test language for validation of the questionnaire. Performance was assessed via Google form surveys distributed to bilingual physicians, which assessed the translation accuracy and clarity of simplified texts provided by ChatGPT 4. Responses from 24 participants showed mixed results. The study underscores the model’s varying success across different languages, emphasizing both potential applications and limitations. ChatGPT 4.0 shows promise in breaking down language barriers in healthcare settings, enhancing patient comprehension of complex medical information. However, the performance is inconsistent across languages, indicating a need for further refinement and more inclusive training of AI models to handle diverse medical contexts and languages. The study highlights the role of LLMs in improving healthcare communication and patient comprehension, while indicating the need for continued advancements in AI technology, particularly in the translation of low-resource languages.